145: Detecting Relapse in Patients with Neuroblastoma: Can Surveillance Programs be Simplified to Decrease Radiation Exposure?
Bibliographic record
Abstract
Neuroblastoma (NBL) is the most common extracranial solid tumour in children, and is responsible for more deaths than any other type of pediatric cancer. Approximately 50% NBL are metastatic at diagnosis and 25% to 35% of all patients will relapse, for which there are generally no curative therapies. Surveillance to detect recurrent disease in NBL patients includes clinical assessment, measurement of urinary catecholamines (UCats), cross-sectional imaging, and I123-meta-idodobenzylguanidine scans (MIBG). Surveillance is costly and results in high cumulative doses of radiation. We hypothesize that relapses may be readily detected with investigations that result in lower doses of cumulative radiation. We sought to determine 1) how relapses were detected (symptoms, physical exam, UCats, MIBG, chest film (CXR), ultrasound (US), CT, and/or MRI) and 2) whether surveillance investigations can identify relapses without using routine CT or MRIs. We reviewed all cases of relapsed NBL at our hospital, a tertiary paediatric centre, between January 2000 and December 2011. 183 children with NBL were treated during the study period. 27% (50 of 183) relapsed, of which 84% (42 of 50) had metastatic disease at diagnosis. Median time from diagnosis to relapse was 1.2 years. 64% (32 of 50) of relapses were detected by surveillance investigations and 36% (18 of 50) due to new symptoms. A median number of nine CTs, four MIBGs, and one MRI were completed between time of diagnosis and relapse. The median effective radiation dose was 99.7 mSv, 84% of which was from CTs and 14.4% from MIBGs. This effective radiation dose was estimated to carry an overall excess cancer risk of >2%. 74% (37 of 50) had new lesions visible by MIBG scan at relapse. Of the remaining 13 relapses, five were detected by elevated UCats, two by bone scan, one by US, and another by CXR. Only four relapses were solely detected by CT and none by MRI: two by routine CT and had no concurrent MIBG, and two by CT ordered due to new symptomatology. Relapsed disease was detected in almost all patients by MIBG scan, UCats, CXR, or US alone. Our results support reduced use of CT imaging in post-therapy surveillance, thereby reducing cumulative radiation doses as the radiation exposure from an MIBG scan is approximately 50% of a CT scan. The intensity of post-therapy surveillance may also be guided by initial disease risk group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".